Dataset for article: From Invisible to Quantifiable: Unmasking Non-Extractable HT2/T2 Glycosides

---------------------------------------------------------------------------------------------------------------------------Dataset for article From Invisible to Quantifiable: Unmasking Non-Extractable HT2/T2 Glycosides---------------------------------------------------------------------------------------------------------------------------------------- * ReadMe version: 1.0 (2026-03-31)* Dataset version: 1.0 (2026-03-31)* Dataset DOI: 10.5281/zenodo.19188378 --------------------------------------------------------------------CONTACT--------------------------------------------------------------------* Milena Stranska* [e-mail]* [phone]* ORCID: 0000-0002-2958-1529* Dept. of Food Analysis and Nutrition. Faculty of Biochemistry and Food Technology, University of chemistry and Technology, Prague* Technicka 5, 166 28, Prague 6, Czech Republic ______Creators______* Milena Stranska (0000-0002-2958-1529), Dept. of Food Analysis and Nutrition. Faculty of Biochemistry and Food Technology, University of chemistry and Technology, Prague* Tereza Dolezalova (0000-0001-8759-1058), Dept. of Food Analysis and Nutrition. Faculty of Biochemistry and Food Technology, University of chemistry and Technology, Prague* Nela Prusova (0000-0002-9829-5200), Dept. of Food Analysis and Nutrition. Faculty of Biochemistry and Food Technology, University of chemistry and Technology, Prague ______Contributors______---------------------------------------------------------------------DATA AVAILABILITY AND ACCESS INSTRUCTIONS--------------------------------------------------------------------* The dataset is openly accessible under the DOI listed above. --------------------------------------------------------------------LICENSE--------------------------------------------------------------------______ReadMe file licence______* ReadMe by Milena Stranska, Tereza Dolezalova and Nela Prusova is licensed under CC BY 4.0* Licence information: https://creativecommons.org/licenses/by/4.0/ ______Dataset licence______* Dataset for article From Invisible to Quantifiable: Unmasking Non-Extractable HT2/T2 Glycosides by Milena Stranska, Tereza Dolezalova and Nela Prusova is licensed under CC BY 4.0* Licence information: https://creativecommons.org/licenses/by/4.0/--------------------------------------------------------------------DESCRIPTION AND METHODOLOGY--------------------------------------------------------------------______About the dataset______This dataset contains experimental data generated during the development and application of an enzymatic hydrolysis method for the release of matrix-associated HT-2 and T-2 mycotoxins from cereal matrices.The dataset includes two main groups of data. The first group consists of optimisation experiments performed on a reference barley sample naturally contaminated with HT-2 and T-2 toxins. Several hydrolysis strategies were tested, varying in enzyme addition scheme, temperature gradient, hydrolysis time, and sample pretreatment. These experiments were used to evaluate the efficiency of mycotoxin release from cereal polysaccharides.The second group of data corresponds to the application of the optimised hydrolysis protocol to naturally contaminated cereal samples, including malting barley and oat-based food products. For each sample, mycotoxin concentrations were determined both before and after enzymatic hydrolysis.Quantification of HT-2 and T-2 toxins was performed using UHPLC-HRMS/MS analysis. The dataset therefore contains raw LC–MS data files, and supporting metadata describing the experimental design, hydrolysis conditions, and analysed samples.The purpose of the dataset is to document the analytical workflow used to estimate the potentially releasable fraction of matrix-associated mycotoxins in cereals under controlled laboratory conditions. ______Ethics______No part of our research project require approval by the ethics board under the Czech Republic legal system. None of the data are considered to be sensitive or personal. ______Sample preparation______Several sample preparation approaches were used in this study during the development and optimisation of the enzymatic hydrolysis procedure. These included different enzyme addition strategies, temperature gradients, hydrolysis times, and matrix pretreatment steps (e.g., boiling or ultrasonication).Following optimisation, the final protocol consisted of boiling pretreatment followed by sequential enzymatic hydrolysis with β-glucanase, glucosidase, α-amylase, and glucoamylase under a controlled temperature gradient.A detailed description of all sample preparation procedures, optimisation experiments, and analytical workflow is provided in the associated publication:Dolezalova T. et al. From Invisible to Quantifiable: Unmasking Non-Extractable HT2/T2 Glycosides. ______Methods of data collection______UHPLC–HRMS/MS analysis of mycotoxins HW1: UltiMate 3000 UHPLC system (Thermo Scientific, USA) coupled to a Q-Exactive Plus Orbitrap high-resolution mass spectrometer (Thermo Scientific, USA) LC separation: column: Acquity UPLC HSS T3 (100 × 2.1 mm, 1.8 µm; Waters, USA) column temperature: 40 °C injection volume: 10 µL mobile phases: A: 5 mM ammonium formate in water with 0.2% formic acid B: 5 mM ammonium formate in methanol with 0.2% formic acid gradient: 10% B → 50% B (1 min) → 100% B (8 min) → re-equilibration at 10% B flow rate: 0.3 mL min⁻¹ MS acquisition: ionisation: ESI positive mode scan mode: Full MS–PRM Full MS resolution: 35,000 FWHM PRM resolution: 17,500 FWHM scan range: m/z 100–1000 ______Methods of data processing______The dataset contains raw LC–MS data acquired using UHPLC–HRMS/MS instrumentation. No additional data processing was applied within this dataset. Raw instrument files correspond to the direct output generated by the Thermo Scientific Q-Exactive Plus mass spectrometer. These files can be processed using vendor software such as TraceFinder or QualBrowser, or other compatible LC–MS data analysis tools. Quantitative results presented in the associated publication were obtained by processing these raw data using isotope-labelled internal standards and calibration procedures described in the article.--------------------------------------------------------------------DATASET STRUCTURE--------------------------------------------------------------------The dataset is structured into thematic folders, where each folder contains raw LC-MS files corresponding to specific experimental conditions. Some acquisition sequences contained multiple experimental conditions. For clarity, raw data files were reorganised into thematic folders (e.g., optimisation, validation, real samples). 01_raw_data ├───method_optimisation │ ├───enzyme_hydrolysis │ │ ├───2023_05_19_optimisation_enzymatic_hydrolysis_1 │ │ ├───2023_07_19_optimisation_enzymatic_hydrolysis_2 │ │ ├───2023_08_21_optimisation_enzymatic_hydrolysis_3 │ │ ├───2024-02-26 optimisation_enzymatic_hydrolysis_4 │ │ ├───2024-04-02 optimisation_enzymatic_hydrolysis_5 │ │ └───2025-08-04_optimisation_enzymatic_hydrolysis_6 │ └───other_tests │ ├───2024-04-17_QuEChERS_reference_value │ │ └───2025-02-26 IAC-reference barley │ └───2025-07-29_Verification_of_individual_enzyme_activity ├───real_samples │ ├───barley │ │ ├───after_hydrolysis │ │ │ ├───2024-09-10_barley_sample_after_hydrolysis-IAC │ │ │ └───2024-10-22_barley_samples_after_hydrolysis-IAC │ │ └───before_hydrolysis │ │ ├───2024-07-29_barley_samples_QuEChERS-prior_hydrolysis │ │ └───2024-09-10_barley_samples_QuEChERS-prior_hydrolysis │ ├───oats │ │ ├───after_hydrolysis │ │ │ ├───2024-09-10_oat_samples_after_hydrolysis-IAC │ │ │ └───2024-09-26_oat_samples_after_hydrolysis-IAC │ │ └───before_hydrolysis │ │ ├───2024-07-29_real_samples-oats-QuEChERS_prior_hydrolysis │ │ └───2024-09-10_real_sample-oat-QuEChERS_prior_hydrolysis │ └───qualitative data_monoglucosides │ ├───2025-06-16-qualitative-data-on-T2-BGlc-IAC-barley │ └───2025-07-17 -qualitative-data-on-HT2-B-Glc-IAC-barley └───validation ├───2024-07-29_thermodegradation_HT2+T2 ├───2024-09-10_repeatability+yields-repeated_extraction+spikes ├───IAC_recovery └───matrix_calibration_LOQ--------------------------------------------------------------------FILENAME STRUCTURE--------------------------------------------------------------------File naming and abbreviations STD – calibration MSTD – calibration for QuEChERS extracts IAC – immunoaffinity column hydr – hydrolysis-------------------------------------------------------------------- --------------------------------------------------------------------FILE TYPES & FORMATS, SW TO OPEN AND DIMENSIONS & UNITS--------------------------------------------------------------------1) Raw LC–MS data Type of data: UHPLC–HRMS/MS chromatographic and mass spectrometric data Original format: .raw (Thermo Scientific proprietary format) Converted format: not provided Software required to open the original files: Thermo Scientific software (e.g. QualBrowser, Xcalibur, or TraceFinder). Other compatible LC–MS data processing tools may also support this format. Data dimensions and units: Mass spectrometry data contain signal intensity as a function of retention time and mass-to-charge ratio (m/z). Typical variables: retention time – minutes (min) mass-to-charge ratio – m/z signal intensity – arbitrary units (instrument response)